Objective To analyze the relationship of protein intake level with high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) in patients with diabetic kidney disease (DKD) and its influence on prognosis. Methods A total of 325 patients with DKD admitted from June 2021 to June 2024 were included and classified into a low protein group and a high protein group. The levels of hs-CRP, IL-6, and TNF-α were compared between the two groups of patients before follow-up and after 1 year of follow-up. The correlation was analyzed by linear mixed model. The incidence of endpoint events during follow-up and disease progression-free survival time were compared between the two groups. Results The inflammatory indicators exhibited no statistical differences between the two groups before follow-up (P>0.05). After 1 year of follow-up, the levels of hs-CRP, IL-6, and TNF-α in the two groups were higher than those before follow-up, and the levels in the high protein group were higher than those in the low protein group (P<0.05). Linear mixed model analysis suggested that the protein intake level, time, and the interaction term of protein intake level × time were correlated with the changes of hs-CRP, IL-6 and TNF-α levels (P<0.05). The incidence rate of endpoint events in the high-protein group during follow-up was 24.84% (40/161), which was significantly higher than 12.80% (21/164) in the low-protein group (χ²=7.724, P=0.005). The disease progression-free survival time was longer in the low-protein group than that in the high-protein group (Log Rank χ²=9.007, P=0.003). Conclusion The level of protein intake in patients with diabetic kidney disease is closely related to inflammatory response and prognosis.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

OBJECTIVE: To compare the bone cement diffusion and clinical effects between conventional percutaneous vertebroplasty(PVP) and the application of positioning reduction and targeted puncture techniques in the treatment of elderly patients with osteoporotic vertebral compression fractures. METHODS: A retrospective comparative study was conducted, analyzing the clinical data of 268 elderly patients with single-level vertebral fractures admitted between January 2021 and March 2023. The patients were divided into two groups:the conventional PVP group (138 cases) and the targeted PVP group (130 cases). Among them, 138 patients in the conventional group were treated by traditional PVP with bilateral approach including 26 males and 112 females, with a mean age of (72.9±4.0) years old. Another 130 patients in the targeted PVP group included 23 males and 107 females, with a mean age of (72.2±7.0) years old;vertebral reduction was first achieved using prone traction and compression reduction technique based on preoperative imaging examination, the operating bed was used to maintain spinal hyper-extension of the spine and puncture the fracture space target to inject bone cement. The adequacy of bone cement filling in the fracture gap was evaluated based on imaging examination. The operation time, the rate of bone cement leakage and the type of leakage, bone cement filling in the fracture area, the amount of cement injection, the thoracolumbar back pain visual analogue scale(VAS), Oswestry disability index(ODI), and the local kyphosis Cobb angle of the fractured vertebra were compared between two groups. RESULTS: The operation time (43.9±5.7) min, bone cement filling (5.3±1.5) ml in the conventional PVP group were higher than the target group (39.3±3.6) min, (4.1±1.7) ml(P<0.05). There were no statistically significant differences in bone cement leakage rate or type(P>0.05). The targeted PVP group achieved sufficient bone cement filling in the fracture area, while the conventional PVP group had 34 cases (25.0%) with insufficient filling in the fracture area(P<0.01). There was no significant difference in VAS, ODI, and local Cobb angle of the fractured vertebra before operation between two groups(P>0.05). The VAS of 3.64±0.94 and ODI of 11.50±0.38 at 3 day after operation in the target group were better than those of the conventional group 4.69±0.78 and 15.06±1.66 (P<0.05). The local Cobb angle (7.51±5.37)° was less than that of the conventional group (11.68±3.98)°(P<0.05). CONCLUSION The application of positioning reduction and targeted puncture techniques in percutaneous vertebroplasty for elderly patients with osteoporotic vertebral compression fractures can restore vertebral height using positioning reduction technique to avoid excessive tension on the intervertebral soft tissue. Targeted puncture technique effectively stabilizes vertebral fractures and achieves adequate bone cement filling, thereby improving surgical outcomes. This technique is safe and effective, representing a new treatment modality.
Humans ; Male ; Female ; Vertebroplasty/methods* ; Aged ; Fractures, Compression/surgery* ; Retrospective Studies ; Spinal Fractures/surgery* ; Osteoporotic Fractures/surgery* ; Aged, 80 and over ; Bone Cements ; Middle Aged

OBJECTIVES: To explore the underlying pharmacological mechanisms and its potential effects of Chinese medicine herbal formula Sini Powder (SNP) on hepatocellular carcinoma (HCC). METHODS: The active components of SNP and their in vivo distribution were identified using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Construction of component-target-disease networks, protein-protein interaction network, Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and molecular docking were employed to analyze the active components and anti-HCC mechanisms of SNP. Cell viability assay and wound healing assay were utilized to confirm the effect of SNP-containing serum (2.5%, 5.0%, 10%, 20%, and 40%), isoprenaline or propranolol (both 10, 100, and 1,000 µ mol/L) on proliferation and migration of HepG 2 or Huh7 cells. Meanwhile, the effect of isoprenaline or propranolol on the β 2 adrenergic receptor (ADRB2) mRNA expression on HepG2 cells were measured by real-time quantitative reverse transcription (RT-qPCR). Mice with subcutaneous tumors were either subjected to chronic restraint stress (CRS) followed by SNP administration (364 mg/mL) or directly treated with SNP (364 mg/mL). These two parallel experiments were performed to validate the effects of SNP on stress responses. Stress-related proteins and hormones were quantified using RT-qPCR, enzyme-linked immunosorbent assay, and immunohistochemistry. Metagenomic sequencing was performed to confirm the influence of SNP on the gut microbiota in the tumor-bearing CRS mice. RESULTS: The distribution of the 12 active components of SNP was confirmed in various tissues and feces. Network pharmacology analysis confirmed the anti-HCC effects of the 5 active components. The potential anti-HCC mechanisms of SNP may involve the epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase Src (SRC) and signal transducer and activator of transcription 3 (STAT3) pathways. SNP-containing serum inhibited the proliferation of HepG2 and Huh7 cells at concentrations of 2.5% and 5.0%, respectively, after 24 h of treatment. Furthermore, SNP suppressed tumor progression in tumor-bearing mice exposed to CRS. SNP treatment also downregulated the expressions of stress-related proteins and pro-inflammatory cytokines, primarily by modulating the gut microbiota. Specifically, the abundance of Alistipes and Prevotella, which belong to the phylum Bacteroidetes, increased in the SNP-treated group, whereas Lachnospira, in the phylum Firmicutes, decreased. CONCLUSION SNP can combat HCC by alleviating stress responses through the regulation of gut microbiota.
Animals ; Gastrointestinal Microbiome/drug effects* ; Liver Neoplasms/microbiology* ; Carcinoma, Hepatocellular/microbiology* ; Humans ; Drugs, Chinese Herbal/therapeutic use* ; Powders ; Cell Proliferation/drug effects* ; Mice ; Molecular Docking Simulation ; Cell Line, Tumor ; Hep G2 Cells ; Receptors, Adrenergic, beta-2/genetics* ; Stress, Physiological/drug effects* ; Cell Movement/drug effects* ; Male ; Protein Interaction Maps/drug effects* ; Cell Survival/drug effects* ; Proto-Oncogene Mas

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract, which increases the incidence of colorectal cancer (CRC). In the pathophysiology of IBD, ubiquitination/deubiquitination plays a critical regulatory function. Josephin domain containing 2 (JOSD2), a deubiquitinating enzyme, controls cell proliferation and carcinogenesis. However, its role in IBD remains unknown. Colitis mice model developed by dextran sodium sulfate (DSS) or colon tissues from individuals with ulcerative colitis and Crohn's disease showed a significant upregulation of JOSD2 expression in the macrophages. JOSD2 deficiency exacerbated the phenotypes of DSS-induced colitis by enhancing colon inflammation. DSS-challenged mice with myeloid-specific JOSD2 deletion developed severe colitis after bone marrow transplantation. Mechanistically, JOSD2 binds to the C-terminal of inosine-5'-monophosphate dehydrogenase 2 (IMPDH2) and preferentially cleaves K63-linked polyubiquitin chains at the K134 site, suppressing IMPDH2 activity and preventing activation of nuclear factor kappa B (NF-κB) and inflammation in macrophages. It was also shown that JOSD2 knockout significantly exacerbated increased azoxymethane (AOM)/DSS-induced CRC, and AAV6-mediated JOSD2 overexpression in macrophages prevented the development of colitis in mice. These outcomes reveal a novel role for JOSD2 in colitis through deubiquitinating IMPDH2, suggesting that targeting JOSD2 is a potential strategy for treating IBD.

Non-invasive body fluids contain a wealth of health-related biomarkers.Monitoring these biomarkers can provide valuable information for disease diagnosis,health management,drug abuse screening,and sports performance optimization.In this work,a carbon nanotube-polysiloxane(CNT-Putty)-based wearable electrochemical sensor was constructed on glove by screen-printing method.This electrode material had not only a simple composition,but also a relatively simple synthesis process.In addition,the electrode exhibited superior electrochemical performance compared to commercial screen-printed electrodes.When applied to uric acid(UA)detection in three different body fluids,the CNT-Putty working electrode demonstrated excellent linearity,selectivity,and a low detection limit.The wearable glove sensor could successfully monitor UA levels in body fluids under varying dietary conditions,indicating its potential for personalized UA monitoring and management.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective To access the current situation of the service capacity of radiation health technical service institutions in Jiangxi Province, analyze the existing problems of these institutions, and provide a scientific basis for standardizing the management of such institutions and improving their service capability. Methods A total of 11 radiation health technical service institutions in Jiangxi Province in the National Occupational Health Technical Service Organization Management Information System were selected as the monitoring objects. During the period from 2022 to 2024, 5-6 technical service institutions were selected each year and comprehensively evaluated and inspected using a checklist formulated by the state. Results Among the 16 quality monitoring results of 11 institutions, 2 (12.5%) were rated as excellent, 12 (75%) as qualified, and 2 (12.5%) as unqualified. The risk level assessment identified 7 (43.75%) high-risk institutions, 9 (56.25%) medium-risk institutions, and 0 (0%) low-risk institutions. Conclusion The overall service capacity of radiation health technical service institutions in Jiangxi Province needs to be improved. Notably, institutions within the health system, such as centers for disease control and prevention, show significant shortcomings in both on-site and laboratory testing capabilities.

Objective To study a method for determining the cumulative dose of low-energy neutrons ( < 100 keV) independently based on a CR-39 detector. Methods According to the theory of track etching kinetics, the differences in the tracks formed by low-energy neutrons or fast neutrons in a BN + CR-39 detector under broad-spectrum neutron irradiation were analyzed. A method was proposed to identify the tracks produced by low-energy neutrons under specific etching conditions while avoiding interference from fast neutron tracks. Results Experimental results demonstrated that the BN + CR-39 detector using TASTRAK PADC CR-39 track-detecting plastic could independently detect the tracks of low-energy neutrons when etched in a 6.25 mol/L NaOH solution for 1 h. The track density showed a good linear relationship with the ambient dose equivalent of low-energy neutrons, and the calibration coefficient was 0.0366 μSv·tr⁻¹·cm². Conclusion The BN + CR-39 detector proposed in this study demonstrated high sensitivity to low-energy neutrons. The track identification method can be used for effective and independent determination of the cumulative dose equivalent of low-energy neutrons.